Many systems analyze data to gain insights into various aspects of healthcare. Insights can be gained by determining relationships among the data. Conventional methods predetermine a few relevant variables to extract from healthcare data for processing and analysis. Based on the few pre-selected variables, relationships are established between various factors such as medical drug, disease, symptoms, etc. Preselecting the variables to focus on limits the ability to discover new or unknown relationships. Preselecting the variables also limits the ability to discover other relevant variables. For example, if the variables are preselected when considering analysis of diabetes, one would be limited to those variables and not realize that the data analysis supports another variable relevant to diabetes that was previously unknown to the healthcare community.